Sample Size and Power Determination

Events

  • 17 May 2013
  • statistics.com
  • Organiser: statistics.com
  • Event Details

Aim of Course:

This course will offer an introduction to sample size and power analysis and will show how to use it simply and effectively to plan the appropriate sample size for a study. The power of a study (the study's ability to detect a treatment effect of a specified size, if it exists) is determined by such factors as the magnitude of the treatment effect, the sample size, alpha (the level of statistical significance required), and (for survival studies) the study duration.


Since some of these factors are under the researcher's control (such as the significance level and sample size) while others are not (such as unknown parameter values that determine effect magnitudes), the goal of power analysis is to balance them as a series of "What if's." For example "What sample size would we need if the treatment reduces the risk of death by 10%, and what sample size would we need if the treatment reduces the risk of death by 20%?" This process of finding a balance among factors can be aided by the use of graphs that allow the researcher to grasp (and communicate) a range of options in a single picture and find the one that strikes the optimal balance between feasible sample size and acceptable power.

Please note this is an online course.

Related Topics

Related Publications

Related Content

Site Footer

Address:

This website is provided by John Wiley & Sons Limited, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ (Company No: 00641132, VAT No: 376766987)

Published features on StatisticsViews.com are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and StatisticsViews.com express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.